Economics of cold emailing

Abstract

This study provides a mathematical model that analyze the factors that determines response rates in bulk cold emails. To test the model, we conducted an empirical analysis based on data from our experiment that included 5,187 cold emails, having an average response rate of 15%. Three key determinants were found: email length combined with the sender's presentation timing, personalization for non-patient buyers, and the time between each product’s features presentation. Specifically, the findings claim that an email under 150 words with a timing introduction of the sender (up to 3 seconds after the start) increases the response rate from 17% to 44%. Personalization, defined as name, company, and location, for non-patient buyers increases the rate to 58%. In contrast, response rate decreases by 17% each increment of 1 second on the average time taken between presenting each product’s features. Unexpectedly, some variables like price discrimination turned out to not have statistical significance on response rates.